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PLASS - Protein-Level ASSembler

BioConda Install Codeship Status for soedinglab/plass Build Status DOI

Plass (Protein-Level ASSembler) is a software to assemble short read sequencing data on a protein level. The main purpose of Plass is the assembly of complex metagenomic datasets. It assembles 10 times more protein residues in soil metagenomes than Megahit. Plass is GPL-licensed open source software that is implemented in C++ and available for Linux and macOS. The software is designed to run on multiple cores. Plass was used to create a Soil Reference Catalog (SRC) and a Marine Eukaryotic Reference Catalog (MERC).

Steinegger M, Mirdita M and Soeding J. Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold. biorxiv, doi: (2018).

Soil Reference Catalog (SRC) and Marine Eukaryotic Reference Catalog (MERC)

SRC was created by assembling 640 soil metagenome samples. MERC was assembled from the the metatranscriptomics datasets created by the TARA ocean expedition. Both catalogues were redundancy reduced to 90% sequence identity at 90% coverage. Each catalog is a single FASTA file containing the sequences, the header identifiers contain the Sequence Read Archive (SRA) identifiers. The catalogues can be downloaded here.

Install static Linux version

Plass can be install via conda or as statically compiled Linux version. Plass requires a 64-bit Linux/MacOS system (check with uname -a | grep x86_64) with at least the SSE4.1 instruction set.

 conda install -c biocore plass 
 # latest static linux build s
 wget; tar xvfz plass-static_sse41.tar.gz; export PATH=$(pwd)/plass/bin/:$PATH

How to assemble

Plass can assemble both paired-end reads (FASTQ) and single reads (FASTA or FASTQ):

  # assemble paired-end reads 
  plass assemble examples/reads_1.fastq.gz examples/reads_2.fastq.gz assembly.fas tmp

  # assemble single-end reads 
  plass assemble examples/reads_1.fastq.gz assembly.fas tmp

Important parameters:

 --min-seq-id         Adjusts the overlap sequence identity threshold
 -e                   E-value threshold for overlaps 
 --skip-n-repeat-kmer Sequence with >= n exact repeating k-mers are ignored
 --num-iterations     Number of iterations of assembly
 --filter-proteins    Switches the neural network protein filter off/on


  plass assemble      Assembles proteins (i:Nucleotides -> o:Proteins)
  plass nuclassemble  Assembles nucleotides *experimental* (i:Nucleotides -> o:Nucleotides)

Assemble using MPI

Plass can be distrubted over several homogeneous computers. However the TMP folder has to be shared between all nodes (e.g. NFS). The following command assembles several nodes:

RUNNER="mpirun -np 42" plass assemble examples/reads_1.fastq.gz examples/reads_2.fastq.gz assembly.fas tmp

Compile from source

Compiling PLASS from source has the advantage that it will be optimized to the specific system, which should improve its performance. To compile PLASS git, g++ (4.6 or higher) and cmake (3.0 or higher) are required. Afterwards, the PLASS binary will be located in the build/bin directory.

  git clone
  cd plass
  git submodule update --init
  mkdir build && cd build
  make -j 4 && make install
  export PATH="$(pwd)/bin/:$PATH"

❗️ If you want to compile PLASS on macOS, please install and use gcc from Homebrew. The default macOS clang compiler does not support OpenMP and PLASS will not be able to run multithreaded. Use the following cmake call:

  CXX="$(brew --prefix)/bin/g++-8" cmake -DCMAKE_BUILD_TYPE=RELEASE -DCMAKE_INSTALL_PREFIX=. ..

Use the docker image

We also provide a Docker image of Plass. You can mount the current directory containing the reads to be assembled and run plass with the following command:

  docker pull soedinglab/plass
  docker run -ti --rm -v "$(pwd):/app" -w /app plass assemble reads_1.fastq reads_2.fastq assembly.fas tmp

Hardware requirements

Plass needs roughly 1 byte of memory per residue to work efficiently. Plass will scale its memory consumption based on the available main memory of the machine. Plass needs a CPU with at least the SSE4.1 instruction set to run.